Metallicity and $α$-abundance for 48 million stars in low-extinction regions in the Milky Way
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arXiv
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| Natura: | Preprint |
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2024
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| _version_ | 1866917936020586496 |
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| author | Hattori, Kohei |
| author_facet | Hattori, Kohei |
| contents | We estimate ([M/H], [$α$/M]) for 48 million giants and dwarfs in low-dust extinction regions from the Gaia DR3 XP spectra by using tree-based machine-learning models trained on APOGEE DR17 and metal-poor star sample \revise{from} Li et al. The root mean square error of our estimation is 0.0890 dex for [M/H] and 0.0436 dex for [$α$/M], when we evaluate our models \revise{on} the test data that are not used in training the models. Because the training data is dominated by giants, our estimation is most reliable for giants. The high-[$α$/M] stars and low-[$α$/M] stars selected by our ([M/H], [$α$/M]) show different kinematical properties for giants and low-temperature dwarfs. We further investigate how our machine-learning models extract information on ([M/H], [$α$/M]). Intriguingly, we find that our models seem to extract information on [$α$/M] from Na D lines (589 nm) and Mg I line (516 nm). This result is understandable given the observed correlation between Na and Mg abundances in the literature. The catalog of ([M/H], [$α$/M]) as well as their associated uncertainties are publicly available online. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_01269 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Metallicity and $α$-abundance for 48 million stars in low-extinction regions in the Milky Way Hattori, Kohei Astrophysics of Galaxies Solar and Stellar Astrophysics We estimate ([M/H], [$α$/M]) for 48 million giants and dwarfs in low-dust extinction regions from the Gaia DR3 XP spectra by using tree-based machine-learning models trained on APOGEE DR17 and metal-poor star sample \revise{from} Li et al. The root mean square error of our estimation is 0.0890 dex for [M/H] and 0.0436 dex for [$α$/M], when we evaluate our models \revise{on} the test data that are not used in training the models. Because the training data is dominated by giants, our estimation is most reliable for giants. The high-[$α$/M] stars and low-[$α$/M] stars selected by our ([M/H], [$α$/M]) show different kinematical properties for giants and low-temperature dwarfs. We further investigate how our machine-learning models extract information on ([M/H], [$α$/M]). Intriguingly, we find that our models seem to extract information on [$α$/M] from Na D lines (589 nm) and Mg I line (516 nm). This result is understandable given the observed correlation between Na and Mg abundances in the literature. The catalog of ([M/H], [$α$/M]) as well as their associated uncertainties are publicly available online. |
| title | Metallicity and $α$-abundance for 48 million stars in low-extinction regions in the Milky Way |
| topic | Astrophysics of Galaxies Solar and Stellar Astrophysics |
| url | https://arxiv.org/abs/2404.01269 |